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Pandas
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
If you did that you could use a built-in library like csv to read and parse the file or you could use a 3rd party library like Pandas. Alternatively, you could store your file as json:
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Again, there are surely bugs in that untested code. You can use the built-in json library to parse that quickly and easily. Libraries like pydantic might make your life even easier.
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InfluxDB
Access the most powerful time series database as a service. Ingest, store, & analyze all types of time series data in a fully-managed, purpose-built database. Keep data forever with low-cost storage and superior data compression.
